from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HpMatchReporting(other_library="sklearnex", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time sklearnex. For instance, a speedup of 2 means that sklearnex is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4 | KNeighborsClassifier_brute_force | predict | 0.067 | 100000 | 1000 | 100 | 3.109389 | 0.029569 | NaN | 0.000257 | 0.003109 | brute | -1 | 5 | 0.743 | 0.210738 | 0.003562 | 0.676 | 14.754728 | 14.756835 |
| 5 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.027766 | 0.002686 | NaN | 0.000029 | 0.027766 | brute | -1 | 5 | 1.000 | 0.008739 | 0.000301 | 0.000 | 3.177146 | 3.179025 |
| 7 | KNeighborsClassifier_brute_force | predict | 0.103 | 100000 | 1000 | 100 | 2.385740 | 0.005925 | NaN | 0.000335 | 0.002386 | brute | 1 | 100 | 0.846 | 0.211071 | 0.003652 | 0.743 | 11.303043 | 11.304735 |
| 13 | KNeighborsClassifier_brute_force | predict | 0.103 | 100000 | 1000 | 100 | 2.347518 | 0.010527 | NaN | 0.000341 | 0.002348 | brute | 1 | 5 | 0.743 | 0.261110 | 0.003644 | 0.846 | 8.990521 | 8.991397 |
| 16 | KNeighborsClassifier_brute_force | predict | 0.067 | 100000 | 1000 | 100 | 1.238940 | 0.007686 | NaN | 0.000646 | 0.001239 | brute | 1 | 1 | 0.676 | 0.213562 | 0.002368 | 0.743 | 5.801300 | 5.801656 |
| 17 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.021695 | 0.000568 | NaN | 0.000037 | 0.021695 | brute | 1 | 1 | 0.000 | 0.009116 | 0.000270 | 1.000 | 2.379967 | 2.381007 |
| 22 | KNeighborsClassifier_brute_force | predict | 0.038 | 100000 | 1000 | 2 | 3.031138 | 0.041008 | NaN | 0.000005 | 0.003031 | brute | -1 | 5 | 0.883 | 0.032786 | 0.000553 | 0.845 | 92.452288 | 92.465459 |
| 25 | KNeighborsClassifier_brute_force | predict | 0.004 | 100000 | 1000 | 2 | 2.314031 | 0.003948 | NaN | 0.000007 | 0.002314 | brute | 1 | 100 | 0.887 | 0.035058 | 0.000922 | 0.883 | 66.006221 | 66.029022 |
| 31 | KNeighborsClassifier_brute_force | predict | 0.004 | 100000 | 1000 | 2 | 2.318878 | 0.004085 | NaN | 0.000007 | 0.002319 | brute | 1 | 5 | 0.883 | 0.077524 | 0.001569 | 0.887 | 29.911812 | 29.917934 |
| 34 | KNeighborsClassifier_brute_force | predict | 0.038 | 100000 | 1000 | 2 | 1.095901 | 0.002899 | NaN | 0.000015 | 0.001096 | brute | 1 | 1 | 0.845 | 0.035396 | 0.001246 | 0.883 | 30.960817 | 30.979992 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.0 | 6.448 | 0.0 | -1 | 1 | 0.050 | 0.0 | 0.248 | 0.248 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.0 | 6.111 | 0.0 | -1 | 5 | 0.049 | 0.0 | 0.266 | 0.266 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.0 | 6.258 | 0.0 | 1 | 100 | 0.050 | 0.0 | 0.255 | 0.255 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.0 | 6.289 | 0.0 | -1 | 100 | 0.049 | 0.0 | 0.258 | 0.258 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.0 | 6.552 | 0.0 | 1 | 5 | 0.050 | 0.0 | 0.245 | 0.245 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.0 | 6.398 | 0.0 | 1 | 1 | 0.050 | 0.0 | 0.250 | 0.250 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.316 | 0.0 | -1 | 1 | 0.010 | 0.0 | 0.513 | 0.513 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.319 | 0.0 | -1 | 5 | 0.010 | 0.0 | 0.494 | 0.494 | See | See |
| 24 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.315 | 0.0 | 1 | 100 | 0.010 | 0.0 | 0.510 | 0.510 | See | See |
| 27 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.317 | 0.0 | -1 | 100 | 0.010 | 0.0 | 0.509 | 0.509 | See | See |
| 30 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.317 | 0.0 | 1 | 5 | 0.010 | 0.0 | 0.502 | 0.502 | See | See |
| 33 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.315 | 0.0 | 1 | 1 | 0.010 | 0.0 | 0.510 | 0.510 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.015 | 0.056 | 0.000 | 0.002 | -1 | 1 | 0.211 | 0.003 | 9.541 | 9.542 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.026 | 0.003 | 0.000 | 0.026 | -1 | 1 | 0.009 | 0.000 | 2.966 | 2.967 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.109 | 0.030 | 0.000 | 0.003 | -1 | 5 | 0.211 | 0.004 | 14.755 | 14.757 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.028 | 0.003 | 0.000 | 0.028 | -1 | 5 | 0.009 | 0.000 | 3.177 | 3.179 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.386 | 0.006 | 0.000 | 0.002 | 1 | 100 | 0.211 | 0.004 | 11.303 | 11.305 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.000 | 0.000 | 0.023 | 1 | 100 | 0.010 | 0.000 | 2.371 | 2.372 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.136 | 0.052 | 0.000 | 0.003 | -1 | 100 | 0.262 | 0.004 | 11.968 | 11.970 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.026 | 0.003 | 0.000 | 0.026 | -1 | 100 | 0.009 | 0.001 | 2.885 | 2.890 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.348 | 0.011 | 0.000 | 0.002 | 1 | 5 | 0.261 | 0.004 | 8.991 | 8.991 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.001 | 0.000 | 0.023 | 1 | 5 | 0.009 | 0.001 | 2.515 | 2.519 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.239 | 0.008 | 0.001 | 0.001 | 1 | 1 | 0.214 | 0.002 | 5.801 | 5.802 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.022 | 0.001 | 0.000 | 0.022 | 1 | 1 | 0.009 | 0.000 | 2.380 | 2.381 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.782 | 0.028 | 0.000 | 0.002 | -1 | 1 | 0.033 | 0.001 | 53.286 | 53.330 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.009 | 0.003 | 0.000 | 0.009 | -1 | 1 | 0.001 | 0.000 | 11.257 | 11.370 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 3.031 | 0.041 | 0.000 | 0.003 | -1 | 5 | 0.033 | 0.001 | 92.452 | 92.465 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.009 | 0.002 | 0.000 | 0.009 | -1 | 5 | 0.001 | 0.000 | 10.557 | 10.637 | See | See |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.314 | 0.004 | 0.000 | 0.002 | 1 | 100 | 0.035 | 0.001 | 66.006 | 66.029 | See | See |
| 26 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.000 | 0.000 | 0.004 | 1 | 100 | 0.001 | 0.000 | 4.128 | 4.262 | See | See |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 3.026 | 0.031 | 0.000 | 0.003 | -1 | 100 | 0.079 | 0.002 | 38.443 | 38.459 | See | See |
| 29 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.011 | 0.002 | 0.000 | 0.011 | -1 | 100 | 0.001 | 0.000 | 10.139 | 10.357 | See | See |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.319 | 0.004 | 0.000 | 0.002 | 1 | 5 | 0.078 | 0.002 | 29.912 | 29.918 | See | See |
| 32 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.000 | 0.000 | 0.004 | 1 | 5 | 0.001 | 0.000 | 3.726 | 3.751 | See | See |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.096 | 0.003 | 0.000 | 0.001 | 1 | 1 | 0.035 | 0.001 | 30.961 | 30.980 | See | See |
| 35 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 1 | 0.001 | 0.000 | 2.045 | 2.088 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 0.011 | 1000000 | 1000 | 10 | 1.727369 | 0.007845 | NaN | 0.000046 | 0.001727 | kd_tree | 1 | 5 | 0.975 | 0.104024 | 0.001276 | 0.964 | 16.605563 | 16.606811 |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.002 | 1000000 | 1000 | 10 | 0.943520 | 0.016693 | NaN | 0.000085 | 0.000944 | kd_tree | -1 | 5 | 0.975 | 0.533486 | 0.001715 | 0.973 | 1.768594 | 1.768603 |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.011 | 1000000 | 1000 | 10 | 0.805566 | 0.004904 | NaN | 0.000099 | 0.000806 | kd_tree | 1 | 1 | 0.964 | 0.182796 | 0.002145 | 0.975 | 4.406916 | 4.407219 |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.002 | 1000000 | 1000 | 10 | 5.153384 | 0.020872 | NaN | 0.000016 | 0.005153 | kd_tree | 1 | 100 | 0.973 | 0.191664 | 0.007276 | 0.975 | 26.887598 | 26.906964 |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.028 | 1000 | 1000 | 2 | 0.023010 | 0.000712 | NaN | 0.000695 | 0.000023 | kd_tree | 1 | 5 | 0.923 | 0.000775 | 0.000149 | 0.895 | 29.693353 | 30.237765 |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.004 | 1000 | 1000 | 2 | 0.024607 | 0.000654 | NaN | 0.000650 | 0.000025 | kd_tree | -1 | 5 | 0.923 | 0.005540 | 0.000724 | 0.919 | 4.441607 | 4.479377 |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.028 | 1000 | 1000 | 2 | 0.021262 | 0.000404 | NaN | 0.000753 | 0.000021 | kd_tree | 1 | 1 | 0.895 | 0.001223 | 0.000229 | 0.923 | 17.384576 | 17.685817 |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.004 | 1000 | 1000 | 2 | 0.037690 | 0.001014 | NaN | 0.000425 | 0.000038 | kd_tree | 1 | 100 | 0.919 | 0.000990 | 0.000315 | 0.923 | 38.061027 | 39.942815 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.607 | 0.016 | 0.022 | 0.0 | 1 | 5 | 0.782 | 0.011 | 4.609 | 4.610 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.406 | 0.019 | 0.018 | 0.0 | -1 | 5 | 0.746 | 0.006 | 5.902 | 5.903 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.289 | 0.058 | 0.019 | 0.0 | -1 | 1 | 0.767 | 0.010 | 5.590 | 5.590 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.773 | 0.062 | 0.021 | 0.0 | 1 | 1 | 0.728 | 0.006 | 5.180 | 5.181 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.802 | 0.030 | 0.021 | 0.0 | 1 | 100 | 0.773 | 0.006 | 4.920 | 4.920 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.791 | 0.064 | 0.021 | 0.0 | -1 | 100 | 0.746 | 0.003 | 5.083 | 5.083 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.026 | 0.0 | 1 | 5 | 0.004 | 0.003 | 0.144 | 0.168 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.026 | 0.0 | -1 | 5 | 0.004 | 0.003 | 0.163 | 0.219 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.027 | 0.0 | -1 | 1 | 0.001 | 0.000 | 0.546 | 0.550 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.025 | 0.0 | 1 | 1 | 0.001 | 0.000 | 0.570 | 0.580 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.026 | 0.0 | 1 | 100 | 0.001 | 0.000 | 0.615 | 0.622 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.027 | 0.0 | -1 | 100 | 0.001 | 0.000 | 0.573 | 0.578 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.727 | 0.008 | 0.000 | 0.002 | 1 | 5 | 0.104 | 0.001 | 16.606 | 16.607 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 5 | 0.000 | 0.000 | 5.958 | 6.392 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.944 | 0.017 | 0.000 | 0.001 | -1 | 5 | 0.533 | 0.002 | 1.769 | 1.769 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.005 | 0.002 | 0.000 | 0.005 | -1 | 5 | 0.001 | 0.000 | 7.944 | 8.406 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.494 | 0.004 | 0.000 | 0.000 | -1 | 1 | 0.104 | 0.001 | 4.770 | 4.770 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 1 | 0.000 | 0.000 | 11.702 | 12.846 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.806 | 0.005 | 0.000 | 0.001 | 1 | 1 | 0.183 | 0.002 | 4.407 | 4.407 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 4.705 | 4.991 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.153 | 0.021 | 0.000 | 0.005 | 1 | 100 | 0.192 | 0.007 | 26.888 | 26.907 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | 1 | 100 | 0.000 | 0.000 | 10.197 | 10.957 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.009 | 0.016 | 0.000 | 0.003 | -1 | 100 | 0.538 | 0.002 | 5.593 | 5.593 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.005 | 0.001 | 0.000 | 0.005 | -1 | 100 | 0.001 | 0.000 | 8.462 | 8.804 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.023 | 0.001 | 0.001 | 0.000 | 1 | 5 | 0.001 | 0.000 | 29.693 | 30.238 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 0.000 | 0.000 | 5.455 | 6.507 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.025 | 0.001 | 0.001 | 0.000 | -1 | 5 | 0.006 | 0.001 | 4.442 | 4.479 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.005 | 0.004 | 0.000 | 0.005 | -1 | 5 | 0.000 | 0.000 | 37.619 | 44.946 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.024 | 0.001 | 0.001 | 0.000 | -1 | 1 | 0.001 | 0.000 | 40.445 | 43.278 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 1 | 0.000 | 0.000 | 19.429 | 23.298 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.021 | 0.000 | 0.001 | 0.000 | 1 | 1 | 0.001 | 0.000 | 17.385 | 17.686 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 5.706 | 6.826 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.038 | 0.001 | 0.000 | 0.000 | 1 | 100 | 0.001 | 0.000 | 38.061 | 39.943 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 0.000 | 0.000 | 5.805 | 7.074 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.037 | 0.001 | 0.000 | 0.000 | -1 | 100 | 0.006 | 0.001 | 6.677 | 6.801 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.001 | 0.000 | 0.002 | -1 | 100 | 0.000 | 0.000 | 18.346 | 21.233 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.629 | 0.006 | 30 | 0.025 | 0.0 | k-means++ | 0.473 | 0.021 | 1.330 | 1.331 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.545 | 0.004 | 30 | 0.029 | 0.0 | random | 0.431 | 0.013 | 1.264 | 1.264 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 6.147 | 0.044 | 30 | 0.130 | 0.0 | k-means++ | 2.898 | 0.010 | 2.121 | 2.121 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 5.812 | 0.024 | 30 | 0.138 | 0.0 | random | 2.742 | 0.018 | 2.120 | 2.120 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.0 | 30 | 0.010 | 0.000 | k-means++ | 0.0 | 0.0 | 10.048 | 11.425 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.0 | 30 | 0.000 | 0.002 | k-means++ | 0.0 | 0.0 | 11.899 | 13.687 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.0 | 30 | 0.010 | 0.000 | random | 0.0 | 0.0 | 9.245 | 10.353 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.0 | 30 | 0.000 | 0.002 | random | 0.0 | 0.0 | 11.972 | 14.021 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.0 | 30 | 0.370 | 0.000 | k-means++ | 0.0 | 0.0 | 7.542 | 8.227 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.0 | 30 | 0.001 | 0.002 | k-means++ | 0.0 | 0.0 | 11.518 | 13.293 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.0 | 30 | 0.412 | 0.000 | random | 0.0 | 0.0 | 6.521 | 7.143 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.0 | 30 | 0.001 | 0.002 | random | 0.0 | 0.0 | 10.219 | 11.391 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | diff_adjusted_rand_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | init | max_iter | n_clusters | n_init | tol | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4 | KMeans_short | predict | 0.001361 | 10000 | 1000 | 2 | 0.002057 | 0.000244 | 20 | 0.007778 | 0.000002 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.000744 | 0.000623 | 0.000110 | -0.000617 | 3.303227 | 3.354649 |
| 7 | KMeans_short | predict | 0.002111 | 10000 | 1000 | 100 | 0.003093 | 0.000290 | 20 | 0.258674 | 0.000003 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.340206 | 0.001317 | 0.000245 | 0.342317 | 2.349128 | 2.389577 |
| 10 | KMeans_short | predict | 0.016992 | 10000 | 1000 | 100 | 0.002997 | 0.000426 | 20 | 0.266897 | 0.000003 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.321348 | 0.001286 | 0.000305 | 0.338339 | 2.330841 | 2.395681 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 0.086 | 0.002 | 20 | 0.002 | 0.0 | random | 0.029 | 0.001 | 2.948 | 2.948 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 0.246 | 0.002 | 20 | 0.001 | 0.0 | k-means++ | 0.095 | 0.001 | 2.603 | 2.604 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 0.222 | 0.002 | 20 | 0.036 | 0.0 | random | 0.122 | 0.002 | 1.816 | 1.816 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 0.663 | 0.010 | 20 | 0.012 | 0.0 | k-means++ | 0.342 | 0.005 | 1.942 | 1.942 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.008 | 0.000 | random | 0.001 | 0.0 | 3.646 | 3.730 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | random | 0.000 | 0.0 | 10.539 | 12.020 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.008 | 0.000 | k-means++ | 0.001 | 0.0 | 3.303 | 3.355 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | k-means++ | 0.000 | 0.0 | 10.447 | 11.889 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.0 | 20 | 0.259 | 0.000 | random | 0.001 | 0.0 | 2.349 | 2.390 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | random | 0.000 | 0.0 | 9.129 | 10.116 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.0 | 20 | 0.267 | 0.000 | k-means++ | 0.001 | 0.0 | 2.331 | 2.396 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | k-means++ | 0.000 | 0.0 | 8.723 | 9.873 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 11.302 | 0.042 | [20] | 0.071 | 0.000 | 1.961 | 0.011 | 5.762 | 5.763 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 0.780 | 0.024 | [27] | 0.103 | 0.001 | 0.762 | 0.028 | 1.023 | 1.023 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | [20] | 2.713 | 0.0 | 0.000 | 0.0 | 0.739 | 0.779 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | [20] | 0.010 | 0.0 | 0.000 | 0.0 | 0.262 | 0.280 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.002 | 0.0 | [27] | 4.422 | 0.0 | 0.003 | 0.0 | 0.556 | 0.558 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | [27] | 0.753 | 0.0 | 0.001 | 0.0 | 0.137 | 0.140 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 0.167 | 0.002 | 0.480 | 0.0 | 0.171 | 0.003 | 0.976 | 0.977 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 1.132 | 0.009 | 0.707 | 0.0 | 0.242 | 0.003 | 4.668 | 4.669 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.01 | 0.0 | 7.978 | 0.0 | 0.017 | 0.001 | 0.581 | 0.581 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 0.00 | 0.0 | 1.019 | 0.0 | 0.000 | 0.000 | 0.673 | 0.775 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 0.00 | 0.0 | 4.854 | 0.0 | 0.000 | 0.000 | 0.639 | 0.700 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 0.00 | 0.0 | 0.012 | 0.0 | 0.000 | 0.000 | 0.601 | 0.754 | See | See |